Determining Prenatal, Early Childhood and Cumulative Long-Term Lead Exposure Using Micro-Spatial Deciduous Dentine Levels
Bibliographic record
Abstract
The aim of this study was to assess the validity of micro-spatial dentine lead (Pb) levels as a biomarker for accurately estimating exposure timing over the prenatal and early childhood periods and long-term cumulative exposure to Pb. In a prospective pregnancy cohort sub-sample of 85 subjects, we compared dentine Pb levels measured using laser ablation-inductively coupled plasma mass spectrometry with Pb concentrations in maternal blood collected in the second and third trimesters, maternal bone, umbilical cord blood, and childhood serial blood samples collected from the ages of 3 months to ≥6 years. We found that Pb levels (as 208Pb:43Ca) in dentine formed at birth were significantly associated with cord blood Pb (Spearman ρ = 0.69; n = 27; p<0.0001). The association of prenatal dentine Pb with maternal patella Pb (Spearman ρ = 0.48; n = 59; p<0.0001) was stronger than that observed for tibia Pb levels (Spearman ρ = 0.35; n = 41; p<0.03). When assessing postnatal exposure, we found that Pb levels in dentine formed at 3 months were significantly associated with Pb concentrations in children's blood collected concurrently (Spearman ρ = 0.64; n = 55; p<0.0001). We also found that mean Pb concentrations in secondary dentine (that is formed from root completion to tooth shedding) correlated positively with cumulative blood lead index (Spearman ρ = 0.38; n = 75; p<0.0007). Overall, our results support that micro-spatial measurements of Pb in dentine can be reliably used to reconstruct Pb exposure timing over the prenatal and early childhood periods, and secondary dentine holds the potential to estimate long-term exposure up to the time the tooth is shed.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".